ChIP and ChIP-Related Techniques: Expanding the Fields of Application and Improving ChIP Performance

Induced proximity labeling and editing for epigenetic research

Epigenetic regulation plays a pivotal role in various biological and disease processes. Two key lines of investigation have been pursued that aim to unravel endogenous epigenetic events at particular genes (probing) and artificially manipulate the epigenetic landscape (editing). The concept of induced proximity has inspired the development of powerful tools for epigenetic research. Induced proximity strategies involve bringing molecular effectors into spatial proximity with specific genomic regions to achieve the probing or manipulation of local epigenetic environments with increased proximity. In this review, we detail the development of induced proximity methods and applications in shedding light on the intricacies of epigenetic regulation.

CSSQ: a ChIP-seq signal quantifier pipeline

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has revolutionized the studies of epigenomes and the massive increase in ChIP-seq datasets calls for robust and user-friendly computational tools for quantitative ChIP-seq. Quantitative ChIP-seq comparisons have been challenging due to noisiness and variations inherent to ChIP-seq and epigenomes. By employing innovative statistical approaches specially catered to ChIP-seq data distribution and sophisticated simulations along with extensive benchmarking studies, we developed and validated CSSQ as a nimble statistical analysis pipeline capable of differential binding analysis across ChIP-seq datasets with high confidence and sensitivity and low false discovery rate with any defined regions. CSSQ models ChIP-seq data as a finite mixture of Gaussians faithfully that reflects ChIP-seq data distribution. By a combination of Anscombe transformation, k-means clustering, estimated maximum normalization, CSSQ minimizes noise and bias from experimental variations. Further, CSSQ utilizes a non-parametric approach and incorporates comparisons under the null hypothesis by unaudited column permutation to perform robust statistical tests to account for fewer replicates of ChIP-seq datasets. In sum, we present CSSQ as a powerful statistical computational pipeline tailored for ChIP-seq data quantitation and a timely addition to the tool kits of differential binding analysis to decipher epigenomes.

ChIP and ChIRP Assays in Ferroptosis

Ferroptosis is characterized by the accumulation of lipid peroxidation driven by iron. As a regulated cell death, ferroptosis plays a critical role in various diseases and exhibits great therapeutic potentials. However, the mechanisms underlying ferroptosis, including its occurrence, execution, and regulation, remain poorly understood, which is necessary for developing effective therapeutic strategies. In this chapter, we summarize chromatin immunoprecipitation (ChIP) assay for the research of proteins-chromatin interactions. Moreover, Chromatin Isolation by RNA Purification (ChIRP) trial is introduced to investigate the interactions between lncRNA and chromatin. The application of ChIP and ChIRP is expected to explore the transcription and epigenetic regulation of ferroptosis deeply for therapeutic benefits.

Transcription Factor Chromatin Immunoprecipitation in Endothelial Cells

Interactions between DNA and proteins are crucial for the regulation of gene expression. Chromatin immunoprecipitation (ChIP) is a powerful technique that allows the study of specific protein-DNA interactions in cultured cells and fresh or fixed tissue. Chromatin is isolated and sheared, and antibodies against the protein(s) of interest are used to isolate specific protein-DNA complexes. Subsequent analysis by real-time polymerase chain reaction (qPCR) or next-generation sequencing (NGS) allows identification and quantification of the co-purified DNA fragments, and NGS also gives insight into the genomic binding sites of a protein. Here we describe a cross-linking ChIP (X-ChIP) protocol, based around the example of a myc-tagged Proline-Rich Homeodomain (PRH) protein expressed in human umbilical vein endothelial cells. We also describe how to analyse specific known or suspected binding sites using quantitative PCR as well as how to analyse genome-wide binding from ChIP sequencing data.

High-Resolution Deep Sequencing of Nascent Transcription in Yeast with BioGRO-seq

RNA biogenesis in eukaryotic cells is a tightly regulated multilayered process in which a diverse set of players act in an orchestrated manner via complex molecular interactions to secure the initial flow of gene expression. Transcription from DNA to RNA is the essential first step in RNA biogenesis, and consists of three main phases: initiation, elongation, and termination. In each phase, transcription factors act on RNA polymerases to modulate their passage along the DNA template in a very precise manner, governed by molecular mechanisms, some of which are not yet fully understood. Genome-scale run-on-based methodologies have been developed with the aim of mapping the position of transcriptionally engaged RNA polymerases. Among them, the BioGRO methodology has been instrumental in advancing our understanding of the transcriptional dynamics in yeast. Here we take the previously known BioGRO method further by coupling it with deep sequencing. BioGRO-seq maps elongating RNA polymerases along the genome with strand specificity and single-nucleotide resolution. BioGRO-seq profiling provides insights into the biogenesis and regulation of not just the canonical protein-coding transcriptome, but also into the often more challenging to study noncoding and unstable transcriptome.

Deciphering molecular interactions by proximity labeling

Many biological processes are executed and regulated through the molecular interactions of proteins and nucleic acids. Proximity labeling (PL) is a technology for tagging the endogenous interaction partners of specific protein 'baits', via genetic fusion to promiscuous enzymes that catalyze the generation of diffusible reactive species in living cells. Tagged molecules that interact with baits can then be enriched and identified by mass spectrometry or nucleic acid sequencing. Here we review the development of PL technologies and highlight studies that have applied PL to the discovery and analysis of molecular interactions. In particular, we focus on the use of PL for mapping protein-protein, protein-RNA and protein-DNA interactions in living cells and organisms.

Nucleosomal embedding reshapes the dynamics of abasic sites

Apurinic/apyrimidinic (AP) sites are the most common DNA lesions, which benefit from a most efficient repair by the base excision pathway. The impact of losing a nucleobase on the conformation and dynamics of B-DNA is well characterized. Yet AP sites seem to present an entirely different chemistry in nucleosomal DNA, with lifetimes reduced up to 100-fold, and the much increased formation of covalent DNA-protein cross-links leading to strand breaks, refractory to repair. We report microsecond range, all-atom molecular dynamics simulations that capture the conformational dynamics of AP sites and their tetrahydrofuran analogs at two symmetrical positions within a nucleosome core particle, starting from a recent crystal structure. Different behaviours between the deoxyribo-based and tetrahydrofuran-type abasic sites are evidenced. The two solvent-exposed lesion sites present contrasted extrahelicities, revealing the crucial role of the position of a defect around the histone core. Our all-atom simulations also identify and quantify the frequency of several spontaneous, non-covalent interactions between AP and positively-charged residues from the histones H2A and H2B tails that prefigure DNA-protein cross-links. Such an in silico mapping of DNA-protein cross-links gives important insights for further experimental studies involving mutagenesis and truncation of histone tails to unravel mechanisms of DPCs formation.

DamID as a versatile tool for understanding gene regulation

The interaction of proteins and RNA with chromatin underlies the regulation of gene expression. The ability to profile easily these interactions is fundamental for understanding chromatin biology in vivo. DNA adenine methyltransferase identification (DamID) profiles genome-wide protein-DNA interactions without antibodies, fixation or protein pull-downs. Recently, DamID has been adapted for applications beyond simple assaying of protein-DNA interactions, such as for studying RNA-chromatin interactions, chromatin accessibility and long-range chromosome interactions. Here, we provide an overview of DamID and introduce improvements to the technology, discuss their applications and compare alternative methodologies.

Summary: This Primer provides an overview of DNA adenine methyltransferase identification (DamID), which is used to profile genome-wide chromatin interactions, and introduces recent improvements to the technology.

Measuring RNA polymerase activity genome-wide with high-resolution run-on-based methods

The biogenesis of RNAs is a multi-layered and highly regulated process that involves a diverse set of players acting in an orchestrated manner throughout the transcription cycle. Transcription initiation, elongation and termination factors act on RNA polymerases to modulate their movement along the DNA template in a very precise manner, more complex than previously anticipated. Genome-scale run-on-based methodologies have been developed to study in detail the position of transcriptionally-engaged RNA polymerases. Genomic run-on (GRO), and its many variants and refinements made over the years, are helping the community to address an increasing amount of scientific questions, spanning an increasing range of organisms and systems. In this review, we aim to summarize the most relevant high throughput methodologies developed to study nascent RNA by run-on methods, compare their main features, advantages and limitations, while putting them in context with alternative ways of studying the transcriptional process.